SOTAVerified

Multi-class Classification

Multi-class classification is a type of supervised learning where the goal is to assign an input to one of three or more distinct classes. Unlike binary classification (which has only two classes), multi-class classification handles multiple labels and uses algorithms like logistic regression, decision trees, random forests, SVMs, or neural networks to predict the correct category based on the features of the input data.

Papers

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Showing 101–150 of 903 papers

TitleStatusHype
Incident duration prediction using a bi-level machine learning framework with outlier removal and intra-extra joint optimisationCode0
Injecting Hierarchical Biological Priors into Graph Neural Networks for Flow Cytometry PredictionCode0
Inverse Design of Metal-Organic Frameworks Using Quantum Natural Language ProcessingCode0
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output CodesCode0
Imbalance Learning for Variable Star ClassificationCode0
Improving the repeatability of deep learning models with Monte Carlo dropoutCode0
Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networksCode0
Auto deep learning for bioacoustic signalsCode0
3DMASC: Accessible, explainable 3D point clouds classification. Application to Bi-spectral Topo-bathymetric lidar dataCode0
HSD Shared Task in VLSP Campaign 2019:Hate Speech Detection for Social GoodCode0
GenSVM: A Generalized Multiclass Support Vector MachineCode0
Generating CCG CategoriesCode0
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and AdaptivityCode0
HemaGraph: Breaking Barriers in Hematologic Single Cell Classification with Graph AttentionCode0
Fuzzy granular approximation classifierCode0
Generalized Consistent Multi-Class Classification with Rejection to be Compatible with Arbitrary LossesCode0
Analysis of French Phonetic Idiosyncrasies for Accent RecognitionCode0
Improving Bias Mitigation through Bias Experts in Natural Language UnderstandingCode0
FlowCyt: A Comparative Study of Deep Learning Approaches for Multi-Class Classification in Flow Cytometry BenchmarkingCode0
InClass Nets: Independent Classifier Networks for Nonparametric Estimation of Conditional Independence Mixture Models and Unsupervised ClassificationCode0
AutoMSC: Automatic Assignment of Mathematics Subject Classification LabelsCode0
Food Classification with Convolutional Neural Networks and Multi-Class Linear Discernment AnalysisCode0
Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class AnnealingCode0
Batch Selection for Multi-Label Classification Guided by Uncertainty and Dynamic Label CorrelationsCode0
Attention-based Context Aggregation Network for Monocular Depth EstimationCode0
A Topological Data Analysis Based ClassifierCode0
Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information NetworksCode0
Achieving Equalized Odds by Resampling Sensitive AttributesCode0
Federated Learning with Only Positive LabelsCode0
Extrapolating Expected Accuracies for Large Multi-Class ProblemsCode0
AMF: Aggregated Mondrian Forests for Online LearningCode0
FA-Net: A Fuzzy Attention-aided Deep Neural Network for Pneumonia Detection in Chest X-RaysCode0
Few-Shot Transfer Learning to improve Chest X-Ray pathology detection using limited tripletsCode0
A matter of attitude: Focusing on positive and active gradients to boost saliency mapsCode0
A Semantic Loss Function for Deep Learning with Symbolic KnowledgeCode0
A Masked Face Classification Benchmark on Low-Resolution Surveillance ImagesCode0
Explaining Convolutional Neural Networks using Softmax Gradient Layer-wise Relevance PropagationCode0
Exponentially Convergent Algorithms for Supervised Matrix FactorizationCode0
Financial Data Analysis with Robust Federated Logistic RegressionCode0
A hybrid algorithm for Bayesian network structure learning with application to multi-label learningCode0
Evaluating approaches for supervised semantic labelingCode0
Adaptive Sampled Softmax with Inverted Multi-Index: Methods, Theory and ApplicationsCode0
Evaluating ML-Based Anomaly Detection Across Datasets of Varied Integrity: A Case StudyCode0
Every Untrue Label is Untrue in its Own Way: Controlling Error Type with the Log Bilinear LossCode0
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text ClassificationCode0
A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised ClassificationCode0
Enhanced Network Embedding with Text InformationCode0
Ensembling Uncertainty Measures to Improve Safety of Black-Box ClassifiersCode0
A Generalized Unbiased Risk Estimator for Learning with Augmented ClassesCode0
Adaptive Gradient Methods Converge Faster with Over-Parameterization (but you should do a line-search)Code0
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All datasetsCOVID-19 CXR DatasetCOVID chest X-rayReuters-52TII-SSRC-23Training and validation dataset of capsule vision 2024 challenge.

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1COVID-CXNetAccuracy (%)94.2—Unverified
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1COVID-ResNetF1 score0.9—Unverified
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1SVM (tficf)Macro F173.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Extra TreesF1-Score93.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Multi-Model EnsembleMean AUC0.99—Unverified